The expected increase in distributed energy resource (DER) penetration at residential levels is promoting new local market frameworks to manage the use of these resources efficiently and improve users' and energy communities' welfare. In this regard, Peer-to-peer (P2P) energy trading and the flexibility market emerge as tentative solutions to address this purpose, empowering the users and energy communities' role in the electricity markets and in the energy transition. This article introduces a deterministic three-stage optimization model to self-manage congestion arising from the high penetration of DERs within an energy community through a local P2P and flexibility market framework. Thus, under a day-ahead time framework, the initial stage considers that each user minimizes their own objective function, which is the energy bought from the grid. Then, in the second stage, the DSO receives the scheduling dispatch from each user through the local market operator and solves an optimal power flow problem to identify possible congestion line issues. If any congestion appears in the second stage, it is managed in the third stage using the flexibility provided by the DERs and the P2P energy trading, considering the user's preferences derived from the first stage problem. The model has been tested in a modified version of the IEEE 33 bus system and shows the capability to mitigate congestion line issues using the flexibility from the storage and PV systems under a P2P energy trading scheme.